Biological vision principles for efficient representation learning from natural images
Project description
💰 Support This Research - Please Donate!
🙏 If this library helps your research or project, please consider donating to support continued development:
💳 DONATE VIA PAYPAL - CLICK HERE
Sparse Coding
🌟 Biological vision principles for efficient representation learning from natural images
Olshausen, B. A., & Field, D. J. (1996) - "Emergence of Simple-Cell Receptive Field Properties by Learning a Sparse Code for Natural Images"
📦 Installation
pip install sparse-coding
🎓 About the Implementation
Implemented by Benedict Chen - bringing foundational AI research to modern Python.
📧 Contact: benedict@benedictchen.com
💰 Support This Work - Donation Appreciated!
This implementation represents hundreds of hours of research and development. If you find it valuable, please consider donating:
💳 DONATE VIA PAYPAL - CLICK HERE
Your support helps maintain and expand these research implementations! 🙏
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
Filter files by name, interpreter, ABI, and platform.
If you're not sure about the file name format, learn more about wheel file names.
Copy a direct link to the current filters
File details
Details for the file sparse_coding-1.0.0.tar.gz.
File metadata
- Download URL: sparse_coding-1.0.0.tar.gz
- Upload date:
- Size: 26.8 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.1.0 CPython/3.13.3+
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
1b443e9f06332af419c5512c7f4309c2671bd88c7c264d661b1a7512326afa8e
|
|
| MD5 |
cf8f9424002d0893d90b2b0ad5ef70d6
|
|
| BLAKE2b-256 |
06e20441675f80a9dc85e7c3bc66a483b8fd15bea96d5da521c8117eb806cc22
|
File details
Details for the file sparse_coding-1.0.0-py3-none-any.whl.
File metadata
- Download URL: sparse_coding-1.0.0-py3-none-any.whl
- Upload date:
- Size: 6.3 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.1.0 CPython/3.13.3+
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
2ad9028f9353c70cf9c8fb2b017a4770bec8903da2ca82fdd3175751d3de22d2
|
|
| MD5 |
07c1bb2ebea193916db29c0057654b41
|
|
| BLAKE2b-256 |
1f798bd97b7f1112320d25037792cc45479400fa199997976aa142e4dbdf3c23
|
